Despite the success of modern Web search engines, challenges remain when it comes to providing people with access to the right information at the right time. In this paper, we desc...
How to endow case-based reasoning systems with effective case adaptation capabilities is a classic problem. A significant impediment to developing automated adaptation procedures i...
Abstract. Effective encoding of information is one of the keys to qualitative problem solving. Our aim is to explore Knowledge representation techniques that capture meaningful wor...
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
There are case-based recommender systems that generate personalized recommendations for users exploiting the knowledge contained in past recommendation cases. These systems assume ...
Conventional approaches to similarity search and case-based retrieval, such as nearest neighbor search, require the specification of a global similarity measure which is typically ...
"Similar problems have similar solutions" is a basic tenet of case-based inference. However this is not satisfied for CBR systems where the task is to achieve original so...
The domain of cookery has been of interest for Case-Based Reasoning (CBR) research for many years since the CHEF case-based planning system in the mid 1980s. This paper returns to ...
Qian Zhang, Rong Hu, Brian Mac Namee, Sarah Jane D...
The use of computational methods is fundamental in cancer research. One of the possibilities is the use of Artificial Intelligence techniques. Several of these techniques have been...
In this paper we present ColibriCook: a CBR system for ontology-based cooking recipe retrieval and adaptation. The system's purpose is to participate in the 1st Computer Cooki...